Neuromonitoring systems and methods

ABSTRACT

Systems, devices, and methods are described for neuromonitoring. A minimum stimulus signal required to elicit a threshold neuromuscular response is determined by delivery of stimulus signals to tissue and detection of neuromuscular responses in muscle tissue. The strength of the delivered stimulus signals is varied, for example by adjusting the current amplitude or pulse width of the signals, and muscle responses are measure, for example by detecting EMG signals. The delivered stimuli and corresponding responses are then used to determine a stimulation threshold. The stimulation threshold may be used to indicate at least one of nerve proximity and pedicle integrity.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.61/730,202, filed Nov. 27, 2012 which is hereby incorporated byreference herein in its entirety.

BACKGROUND

The risk of injury to a nerve is a concern when performing surgicalprocedures, including minimally-invasive procedures, within closeproximity to the spine or nerves. Surgeons increasingly rely onneuromonitoring techniques to monitor the nerves during such surgeriesin order to avoid inadvertently injuring or contacting a nerve. Priordevices have been developed to help surgeons avoid contacting anddamaging nerves during these procedures, but improvements are needed forenhancing the accuracy and speed of those devices.

Devices and methods are particularly needed for providing quick and safeneuromonitoring during surgery. Such devices should provide preciseinformation regarding the proximity of nerves to surgical instruments orthe integrity of vertebral bone quickly in order to provide earlywarning and avoid damage to the nerves. Both patient safety and the timerequired to provide the necessary information to the surgeon can beimproved by reducing the number of electrical stimulations delivered toa patient or measurements that are required to produce an indication ofnerve proximity or bone integrity.

SUMMARY

Disclosed herein are systems, devices, and methods for neuromonitoring,particularly neuromonitoring to avoid contacting or damaging nerves orcausing patient discomfort during surgical procedures.

According to some implementations, a method for neuromonitoring isprovided to identify by estimation the minimum current amplitudenecessary to cause a muscle EMG response in a patient. In general, themethod includes providing a plurality of stimulation pulses to patientanatomy near a desired surgical site, measuring the patient's response(e.g., neuromuscular response) to each of the pulses, and estimatingfrom those responses the minimum current or other stimulation amountnecessary to cause the response. In certain embodiments, each of theplurality of pulses is applied with sufficient energy to cause an EMGresponse in the patient. In certain applications that is achieved byadjusting the current amplitude, pulse width, or both, so as to deliverenergy that exceeds an expected threshold energy level for theparticular nerve or nerves in the region of the surgical site.

According to one aspect, a method for neuromonitoring includes the stepsof (a) delivering a first stimulus signal having a first amplitude and asecond stimulus signal having a second amplitude to tissue including oradjacent to a nerve, the first amplitude being different from the secondamplitude; (2) detecting, in muscle tissue, a first neuromuscularresponse in response to the first stimulus signal and a secondneuromuscular response in response to the second stimulus signal; (3)calculating a stimulation threshold for the nerve from the first andsecond stimulus signal amplitudes and the first and second neuromuscularresponses, the stimulation threshold being an estimate of a minimumstimulus level required to elicit a neuromuscular response greater thanor equal to a predetermined threshold; and (4) communicating to a useran indicator of the stimulation threshold to indicate at least one ofnerve proximity and pedicle integrity. Additional stimulation signalsmay also be used.

In certain implementations, each of the first and second neuromuscularresponses is greater than or equal to a predetermined threshold, whilein other implementations one of the first and second neuromuscularresponses is greater than or equal to the predetermined threshold, andthe other of the first and second neuromuscular responses is less thanthe predetermined threshold. The first and second neuromuscularresponses may be detected using EMG, and the predetermined threshold maycorrespond to a voltage level of detected EMG signals or may correspondto a level of correlation calculated from detected EMG signals. Themethod may include cross-correlating the detected EMG signals with anEMG response template (e.g., a predetermined template), and thepredetermined threshold may be a level of correlation between thedetected EMG signals and the EMG response template.

In certain implementations, the calculating step includes calculating alinear function from the first and second stimulus signal amplitudes andthe first and second neuromuscular responses and determining thestimulation threshold from the linear function. In otherimplementations, the calculating step includes calculating a curve fitfrom the first and second stimulus signal amplitudes and the first andsecond neuromuscular responses and determining the stimulation thresholdfrom the curve fit. The curve fit may be a sigmoid function, or may beanother suitable function.

In certain implementations, the method further includes delivering aplurality of test stimulus signals to the tissue and detecting aplurality of test neuromuscular responses, each of the plurality of testneuromuscular responses corresponding to one of the plurality of teststimulus signals. Each of the plurality of test stimulus signals mayhave an amplitude that is greater than a preceding test stimulus signal,and the amplitudes of the test stimulus signals may increase at aconstant increments or may increase at varying increments. The first andsecond stimulus signals may be selected based on the test stimulussignals and test neuromuscular responses. A curve fit may be calculatedusing the test stimulus signals and test neuromuscular responses. Incertain implementations, the first and second stimulus signals areselected from test stimulus signals that elicit test neuromuscularresponses that meet the predetermined threshold. In otherimplementations, one of the first and second stimulus signals isselected from test stimulus signals that elicit test neuromuscularresponses that are greater than or equal to the predetermined threshold,and the other of the first and second stimulus signals is selected fromtest stimulus signals that do not elicit test neuromuscular responsesthat are greater than or equal to the predetermined threshold.

In certain implementations, detecting the first and second neuromuscularresponses includes measuring neuromuscular activity in the muscle tissueduring predetermined time windows, and the time windows may be offsetfrom delivery times of the first and second stimulus signals. Thepredetermined time windows may be offset based on a signal transit timeassociated with the nerve and the muscle tissue.

In certain implementations, the first neuromuscular response is detectedbefore the second stimulus signal is delivered, and the amplitude of thesecond stimulus signal may be adjusted based on the first neuromuscularresponse. In other implementations, the second stimulus signal isdelivered before the first neuromuscular response is detected, anddelivery of the first and second stimulus signals may be offset by anamount that is greater than or equal to a refractory period of the nerveand the muscle tissue. In certain implementations, the amplitude of thesecond stimulation signal may be double the amplitude of the firststimulation signal.

In certain implementations, the communicating step includes displayingthe indicator for one of nerve proximity or pedicle integrity. Theindicator may include a color-coded indicator that indicates one rangeof a plurality of amplitude ranges, and the stimulation threshold fallswithin the indicated range. The color-coded indicator may include atleast three ranges, including at least one safe region and at least oneunsafe region.

According to one aspect, a system for neuromonitoring includes a (1)surgical instrument for delivering stimulus signals to tissue includingor adjacent to a nerve and (2) a processing system that includes (A) adetection module configured to detect, in muscle tissue, a firstneuromuscular response in response to a first stimulus signal having afirst amplitude and to detect a second neuromuscular response inresponse to a second stimulus signal having a second amplitude; (B) aprocessing module in communication with the detection module andconfigured to calculate a stimulation threshold for the nerve from thefirst and second stimulus signal amplitudes and the first and secondneuromuscular responses, the stimulation threshold being an estimate ofa minimum stimulus level required to elicit a neuromuscular responsegreater than or equal to a predetermined threshold; and (C) acommunications module in communication with the processing module andconfigured to communicate an indicator of the stimulation threshold to auser to indicate at least one of nerve proximity and pedicle integrity.

In certain implementations, the surgical instrument includes a probecoupled to an electrical source, and a stimulating electrode may bedisposed on a distal end of the probe. The detection module may includea sensing electrode configured to detect EMG signals, and the sensingelectrode may include a surface EMG electrode or a needle EMG electrode.In certain implementations, the detection module is configured to detectneuromuscular responses in the muscle tissue during predetermined timewindows, and the predetermined time windows may be offset from deliverytimes of the first and second stimulus signals. The predetermined timewindows may be offset based on a signal transit time associated with thenerve and the muscle tissue.

In certain implementations, the processing module is configured tocalculate a linear function from the first and second stimulus signalamplitudes and the first and second neuromuscular responses, and theprocessing module may be further configured to determine the thresholdstimulation from the linear function. In other implementations, theprocessing module is configured to calculate a curve fit from the firstand second stimulus signal amplitudes and the first and secondneuromuscular responses, and the processing module may be furtherconfigured to determine the threshold stimulation from the curve fit.The curve fit may be a sigmoid function.

In certain implementations, the detection module is configured to applya voltage level threshold to detected EMG signals. In otherimplementations, the detection module is configured to cross-correlatedetected EMG signals with an EMG response template, and the detectionmodule may be configured to apply a correlation level threshold to thecross-correlation.

In certain implementations, the processing system includes a controlmodule configured to select the amplitudes of the first and secondstimulus signals, and the control module may be configured to select theamplitudes from a curve fit of test stimulus signal amplitudes and testneuromuscular responses.

According to one aspect, a system for neuromonitoring includes (1) meansfor delivering stimulus signals to tissue including or adjacent to anerve; (2) means for detecting, in muscle tissue, a first neuromuscularresponse in response to a first stimulus signal having a firstamplitude; (3) means for detecting, in the muscle tissue, a secondneuromuscular response in response to a second stimulus signal having asecond amplitude; (4) means for calculating a stimulation threshold forthe nerve from the first and second stimulus signal amplitudes and thefirst and second neuromuscular responses, the stimulation thresholdbeing an estimate of a minimum stimulus level required to elicit aneuromuscular response greater than or equal to a predeterminedthreshold; and (5) means for communicating an indicator of thestimulation threshold to a user to indicate at least one of nerveproximity and pedicle integrity.

In certain implementations, the means for delivering stimulus signalsincludes a probe coupled to an electrical source means, and astimulating means may be disposed on a distal end of the probe. Incertain implementations, the means for detecting includes a means forsensing EMG signals, and the means for sensing may include a surface EMGelectrode or a needle EMG electrode.

In certain implementations, the means for detecting includes means fordetecting neuromuscular responses in the muscle tissue duringpredetermined time windows, and the predetermined time windows may beoffset from delivery times of the first and second stimulus signals. Thepredetermined time windows may be offset based on a signal transit timeassociated with the nerve and the muscle tissue.

In certain implementations, the means for calculating includes means forcalculating a linear function from the first and second stimulus signalamplitudes and the first and second neuromuscular responses, and themeans for processing may include means for determining the thresholdstimulation from the linear function. In other implementations, themeans for calculating includes means for calculating a curve fit fromthe first and second stimulus signal amplitudes and the first and secondneuromuscular responses, and the means for processing may include meansfor determining the threshold stimulation from the curve fit. The curvefit may be a sigmoid function.

In certain implementations, the means for detecting includes means forapplying a voltage threshold to detected EMG signals. In otherimplementations, the means for detecting includes means forcross-correlating detected EMG signals with an EMG response template,and the means for detecting may include means for applying a correlationlevel threshold to the cross-correlation. In certain implementations,the system includes a means for selecting the amplitudes of the firstand second stimulus signals, and the means for selecting may includemeans for selecting the amplitudes from a curve fit of test stimulussignal amplitudes and test neuromuscular responses.

According to one aspect, a method for neuromonitoring includes the stepsof (1) delivering a first stimulus signal having a first pulse width anda second stimulus signal having a second pulse width to tissue includingor adjacent to a nerve, the first pulse width being different from thesecond pulse width; (2) detecting, in muscle tissue, a firstneuromuscular response in response to the first stimulus signal and asecond neuromuscular response in response to the second stimulus signal;(3) determining a stimulation threshold for the nerve from the first andsecond pulse widths and the first and second neuromuscular responses,the stimulation threshold being an estimate of a minimum pulse widthrequired to elicit a neuromuscular response greater than or equal to apredetermined threshold; and (4) communicating to a user an indicator ofthe stimulation threshold to indicate at least one of nerve proximityand pedicle integrity.

In certain embodiments, the first and second stimulus signals aredelivered at a constant current, and the first and second stimulussignals may be delivered at a constant voltage.

In certain implementations, the method includes delivering a pluralityof stimulus signals, each stimulus signal having a larger pulse widththan a preceding stimulus signal. The pulse width of the stimulussignals in the plurality of stimulus signals may increase at a constantincrement or may increase at varying increments. Delivering a pluralityof stimulus signals may include delivering stimulus signals until aneuromuscular response greater than or equal to the predeterminedthreshold is detected. The second neuromuscular response may be thefirst detected neuromuscular response greater than or equal to thepredetermined threshold, and communicating an indicator may includecommunicating the second pulse width to the user.

In certain implementations, the first and second pulse widths define aninitial pulse width range, and determining a stimulation thresholdincludes delivering stimulus signals having pulse widths selected fromwithin the initial pulse width range to determine a minimum pulse widthrequired to elicit a neuromuscular response greater than or equal to thepredetermined threshold. Delivering stimulus signals having pulse widthsselected from within the initial pulse width range may includedelivering a sequence of stimulus signals having pulse widths thateither increase by a constant increment or decrease by a constantdecrement. In certain implementations, the sequence of stimulus signalsis delivered from a first stimulus signal near a lower bound of theinitial pulse width range and increasing the pulse width of subsequentstimulus signals to a value near an upper bound of the initial pulsewidth range. In other implementations, the sequence of stimulus signalsis delivered from a first stimulus signal near an upper bound of theinitial pulse width range and decreasing the pulse width of subsequentstimulus signals to a value near a lower bound of the initial pulsewidth range. In certain implementations, a subsequent stimulus pulse isdelivered having a pulse width equal to a midpoint of the initial pulsewidth range.

In certain implementations, communicating an indicator includesdisplaying an indication of electric charge, and the indication ofelectric charge may be displayed in coulombs. In other implementations,communicating an indicator includes displaying a distance between thenerve and a surgical instrument, and the method may include calculatingthe displayed distance from an electric charge corresponding to thestimulation threshold. In other implementations, communicating anindicator includes displaying a pulse width corresponding to thestimulation threshold. The method may also include communicating atleast one of a constant current or constant voltage at which the firstand second stimulus signals are delivered.

In certain implementations, the first neuromuscular response is detectedbefore the second stimulus signal is delivered. In otherimplementations, the second stimulus pulse is delivered before the firstneuromuscular response is detected, and an offset time between deliveryof the first stimulus pulse and delivery of the second stimulus pulsemay be greater than or equal to a refractory period associated with thenerve and the muscle tissue.

According to one aspect, a system for neuromonitoring includes (1) asurgical instrument for delivering stimulus signals to tissue includingor adjacent to a nerve and a processing system including (A) a detectionmodule configured to detect, in muscle tissue, a first neuromuscularresponse to a first stimulus signal having a first pulse width and todetect a second neuromuscular response to a second stimulus signalhaving a second pulse width; (B) a processing module in communicationwith the detection module and configured to determine a stimulationthreshold for the nerve from the first and second stimulus signal pulsewidths and the first and second neuromuscular responses, the stimulationthreshold being an estimate of a minimum pulse width required to elicita neuromuscular response greater than or equal to a predeterminedthreshold; and (C) a communications module in communication with theprocessing module and configured to communicate an indicator of thestimulation threshold to indicate at least one of nerve proximity andpedicle integrity.

In certain implementations, the surgical instrument includes a probecoupled to an electrical source, and a stimulating electrode may bedisposed on a distal end of the probe. In certain implementations, thedetection module includes a sensing electrode configured to detect EMGsignals, and the sensing electrode may be a surface EMG electrode or aneedle EMG electrode. In certain implementations, the detection moduleis configured to detect neuromuscular responses in the muscle tissueduring predetermined time windows, and the predetermined time windowsmay be offset from delivery times of the first and second stimulussignals. The predetermined time windows may be offset based on a signaltransit time associated with the nerve and the muscle tissue.

In certain implementations, the processing system includes a controlmodule configured to deliver a plurality of stimulus signals, eachstimulus signal having a larger pulse width than a preceding stimulussignal. The control module may be configured to increase the pulse widthof the stimulus signals in the plurality of stimulus signals at aconstant increment or at varying increments.

In certain implementations, the detection module is configured to applya voltage level threshold to detected EMG signals. In otherimplementations, the detection module is configured to cross-correlatedetected EMG signals with an EMG response template, and the detectionmodule may be configured to apply a correlation level threshold to thecross-correlation.

In certain implementations, the communications module includes a displayconfigured to display an indication of electric charge, and theindication of electric charge may be displayed in coulombs. In otherimplementations, the communications module includes a display configuredto display a distance between the nerve and the surgical instrument, andthe processing module may be configured to calculate the displayeddistance from the stimulation threshold. In other implementations, thecommunications module includes a display configured to display a pulsewidth corresponding to the stimulation threshold. In certainimplementations, the communications module is further configured tocommunicate at least one of a constant current or a constant voltage atwhich the first and second stimulus signals are delivered.

According to one aspect, a neuromonitoring system includes (1) means fordelivering stimulus signals to tissue including or adjacent to a nerve;(2) means for detecting, in muscle tissue, a first neuromuscularresponse to a first stimulus signal having a first pulse width; (3)means for detecting, in muscle tissue, a second neuromuscular responseto a second stimulus signal having a second pulse width; (4) means fordetermining a stimulation threshold for the nerve from the first andsecond stimulus signal pulse widths and the first and secondneuromuscular responses, the stimulation threshold being an estimate ofa minimum pulse width required to elicit a neuromuscular responsegreater than or equal to a predetermined threshold; and (5) means forcommunicating an indicator of the stimulation threshold to indicate atleast one of nerve proximity and pedicle integrity.

In certain implementations, the means for delivering stimulus signalsincludes a probe coupled to an electrical source means, and astimulating means may be disposed on a distal end of the probe. Incertain implementations, the means for detecting includes a means forsensing EMG signals, and the means for sensing may include a surface EMGelectrode or a needle EMG electrode.

In certain implementations, the means for detecting includes a means fordetecting neuromuscular responses in the muscle tissue duringpredetermined time windows, and the predetermined time windows areoffset from delivery times of the first and second stimulus signals. Thepredetermined time windows may be offset based on a signal transit timeassociated with the nerve and the muscle tissue.

In certain implementations, the means for determining includes a controlmeans for delivering a plurality of stimulus signals, each stimulussignal having a larger pulse width than a preceding stimulus signal. Thecontrol means may include means for increasing the pulse width of thestimulus signals in the plurality of stimulus signals at a constantincrement or at varying increments.

In certain implementations, the means for detecting includes means forapplying a voltage level threshold to detected EMG signals. In otherimplementations, the means for detecting includes means forcross-correlating detected EMG signals with an EMG response template,and the means for detecting may include means for applying a correlationlevel threshold to the cross-correlation.

In certain implementations, the means for communicating includes meansfor displaying an indication of electric charge, and the indication ofelectric charge may be displayed in coulombs. In other implementations,the means for communicating includes means for displaying a distancebetween the nerve and the means for delivering stimulus signals, and themeans for processing may include means for calculating the displayeddistance from the stimulation threshold. In other implementations, themeans for communicating includes means for displaying a pulse widthcorresponding to the stimulation threshold. In certain implementations,the means for communicating includes means for communicating at leastone of a constant current or a constant voltage at which the first andsecond stimulus signals are delivered.

According to one aspect, a system for neuromonitoring includes (1) asurgical accessory having at least one stimulation electrode; (2) aprocessing system configured to (A) stimulate the at least onestimulation electrode with an electrical stimulation signal havingpulses, (B) measure a neuromuscular response caused by nervesdepolarized by the stimulation signal, and (C) automatically determine astimulation threshold of the nerves by automatically adjusting a pulsewidth of the stimulation signal; and (3) a communication moduleconfigured to communicate to a user an indication of the stimulationthreshold to indicate at least one of nerve proximity and pedicleintegrity.

In certain implementations, the processing system is configured toautomatically adjust the pulse width by variable amounts, while in otherimplementations the processing system is configured to automaticallyadjust the pulse width by constant amounts. In certain implementations,the processing system is configured to maintain the stimulation signalat a fixed current amplitude, while in other implementations theprocessing system is configured to vary an amplitude of the stimulationsignal by either variable or constant amounts.

In certain implementations, the processing system is configured with aplurality of predetermined ranges and the communication module isconfigured to communicate to the user by indicating which one of thepredetermined ranges the stimulation threshold falls within. Theplurality of predetermined ranges may include ranges of pulse widths, orthe plurality of predetermined ranges may include ranges of coulombsindicating the total charge delivered by the stimulation electrode.

In certain implementations, the communication module is configured tocommunicate to the user by displaying information on at least first andsecond display screens. The communication module may be configured todisplay the indicator on the first display screen and an EMG waveformcorresponding to the measurement on the second display screen.

In certain implementations, the processing system is configured toautomatically determine the stimulation threshold by calculating thestimulation threshold from a plurality of stimulation pulses havingvariable pulse width and measured responses corresponding to theplurality of stimulation pulses.

According to one aspect, a method for neuromonitoring includes the stepsof (1) delivering by a stimulating electrode located on a surgicalaccessory a plurality of stimulation signals to tissue including oradjacent to a nerve; (2) detecting by a sensor associated with muscletissue associated with the nerve a plurality of neuromuscular responseselicited by the stimulation signals; (3) calculating a stimulationthreshold for the nerve by extrapolation from the neuromuscularresponses; and (4) communicating an indicator of the stimulationthreshold to a user to indicate one of nerve proximity and pedicleintegrity.

Variations and modifications of these embodiments will occur to those ofskill in the art after reviewing this disclosure. The foregoing featuresand aspects may be implemented, in any combination and subcombination(including multiple dependent combinations and subcombinations), withone or more other features described herein. The various featuresdescribed or illustrated herein, including any components thereof, maybe combined or integrated in other systems. Moreover, certain featuresmay be omitted or not implemented.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects and advantages will be apparent uponconsideration of the following detailed description, taken inconjunction with the accompanying drawings, in which like referencecharacters refer to like parts throughout.

FIG. 1 depicts an illustrative trend of EMG responses.

FIG. 2 depicts an illustrative surgical monitoring system coupled to asurgical instrument and electrode.

FIG. 3 depicts illustrative detected EMG responses for multiple stimulussignals.

FIG. 4 depicts an illustrative amplitude threshold applied to detectedEMG signals.

FIG. 5 depicts an illustrative cross-correlation of detected EMG signalsand an illustrative threshold of applied to the cross-correlation.

FIGS. 6-8 depict illustrative estimations of a threshold stimulationusing linear modeling.

FIG. 9 depicts an illustrative estimation of a threshold stimulationusing curve-fitting modeling.

FIG. 10 depicts an illustrative sequence of test stimulus signals and acorresponding illustrative sequence of detected EMG responses.

FIGS. 11 and 12 depict illustrative sequences of stimulus signals andcorresponding detected EMG responses.

FIG. 13 shows an illustrative comparison of stimulus signals havingincreasing currents and stimulus signals having increasing pulse widths.

FIG. 14 shows an illustrative strength-duration curve.

FIGS. 15-19 depict illustrative sequences of stimulus signals andcorresponding detected EMG responses.

FIG. 20 depicts an illustrative surgical monitoring system.

FIG. 21 depicts an illustrative display screen having various modewindows.

FIGS. 22-24 depict illustrative display screens having mode windowsdocked to various regions within the respective display screens.

FIGS. 25 and 26 depict various illustrative displays for use with thesurgeon view.

FIGS. 27-30 depict various illustrative dials displayed during asurgical procedure.

FIG. 31 depicts an illustrative display for use with the monitoristview.

FIG. 32 depicts an illustrative sub-window indicating the responseamplitude threshold.

FIG. 33 depicts an illustrative sub-window for artifact rejection.

FIG. 34 depicts an illustrative interface for adjusting thresholdranges.

DETAILED DESCRIPTION

To provide an overall understanding of the systems, devices, and methodsdescribed herein, certain illustrative embodiments will be described.Although the embodiments and features described herein are specificallydescribed for use in connection with spinal surgical procedures, it willbe understood that the system components, connection mechanisms,surgical procedures, and other features outlined below may be combinedwith one another in any suitable manner and may be adapted and appliedto systems to be used in other surgical procedures performed in theproximity of neural structures where nerve avoidance, detection, ormapping is desired, including, but not limited to spine surgeries, brainsurgeries, carotid endarterectomy, otolaryngology procedures such asacoustic neuroma resection, parotidectomy, nerve surgery, or any othersuitable surgical procedures.

The present disclosure relates to systems, devices, and methods forintraoperative neuromonitoring (IONM) of any of evoked potential (EP),transcranial electrical motor evoked potential (TceMEP),electromyography (EMG), and electroencephalogram (EEG) signals.Intraoperative neuromonitoring reduces the risk of permanent injury toneural structures during surgical procedures. Changes or abnormalitiesin the recorded signals may indicate that the surgical procedure isaffecting the neural structure. The systems, devices, and methods of thepresent disclosure measure and display the electrical signals generatedby any of muscles, the central nervous system, and peripheral nerves andacquire the data necessary to perform intraoperative monitoring ofneural pathways to prevent damage to neural structures during surgicalprocedures. It will be appreciated that the systems, devices, andmethods of the present disclosure can be adapted for use in pre- andpost-operative procedures in addition to or in place of intraoperativeprocedures.

Electrical nerve assessment can be employed during a lateral approachspinal surgery in which instruments are advanced to the spine in atrans-psoas approach through a user's side. Such an approach may bepreferred to gain access to the spine, for example to vertebralpedicles, and to provide advantageous angles for insertion of pediclescrews. Instruments approaching the spine laterally must be advancedwith caution, as sensitive nerve roots from the spinal cord exit thespine in lateral directions, and harm or unintentional stimulation ofthese nerve roots can cause pain or damage. In order to avoid unwantedcontact with these nerves, electrical assessment procedures discussedherein may be used to determine the proximity of nerves and warn asurgeon if an instrument is approaching too near to one or more of thenerve roots. By applying stimulus currents to the instruments andmeasuring the responses in muscles innervated by the nerve roots, suchprocesses can guide a surgeon through the lateral muscles and to thespine without unintentionally contacting or damaging the nerves.

These electrical nerve assessment processes may also be used to evaluateand monitor the integrity of a pedicle during tapping, insertion, andfinal placement of a spinal screw once instruments are advanced to thespine. The pedicles of a vertebra form the medial and lateral boundariesof the canal through the spine that houses the spinal cord, and lateralnerve roots extend outward from the spinal cord near the pedicles. Anyscrew or other instrument advanced into the pedicle is, preferably,precisely inserted so as to avoid compromising the walls of the pedicleand exposing the screw or instrument to the sensitive nerve tissue. Inorder to evaluate the integrity of a pedicle during these sensitiveprocesses, an electrical stimulus and muscle monitoring approach such asthe approaches discussed herein may be employed. The bone material thatforms the pedicle insulates an interior channel through the pedicle, andinstruments placed into the channel, from the sensitive surroundingnerves. Thus, an uncompromised pedicle will prevent surrounding nervesfrom becoming stimulated by an electrical stimulus applied to theinterior channel. However, if the pedicle walls are compromised ornearly compromised during drilling or placement of an instrument, theinsulation may be compromised and may result in surrounding nerves beingstimulated from an internal stimulus pulse. During or after tapping thepedicle and placing a screw, the electrical assessment proceduresdiscussed herein may be used to apply stimulus to a pedicle or to ascrew placed in the pedicle, and responses of muscles innervated bylocal nerves can be used to identify damaged or compromised pedicles.

Electrical stimulus applied to a patient's tissue should be appliedcarefully. Application of too much current can cause damage to tissueand to nerves within the tissue, and can cause pain to the patient.However, multiple test stimulations may be needed to accurately detectand assess the proximity or location of nerves within the tissue beingstimulated. This establishes a trade-off between delivering enoughstimulation and detecting enough muscle responses to that stimulation inorder to accurately provide a surgeon with precise information on nerveproximity and limiting the number of stimulations delivered in order toavoid causing unnecessary harm to a patient. If too few stimulations areused, the data provided to a surgeon may not be entirely accurate, andmay lead to mistakes made during surgery due to inadequate nerveproximity information. On the other hand, if too many stimulations aredelivered, the overall amount of current and electrical energy deliveredto the patient's tissue may cause unwanted side effects. This trade-offmay be managed by utilizing an estimation technique that allows adequateinformation to be calculated for providing to a surgeon while stilllimiting or decreasing the number of stimulations required to obtainthat information.

FIG. 1 depicts a graph 10 showing a standard neuromuscular EMG responseprofile of a muscle innervated by a nerve near the source of a deliveredstimulus signal. As shown in the trend 12 in the graph 10, the magnitudeof an EMG response sensed at the muscle tissue increases as the stimulussignal level increases near a nerve that innervates the monitoredmuscle. The increase in stimulus signal level may be the result ofadjusting one or more of current voltage, charge, or pulse width of adelivered stimulus. When the delivered stimulus signal is small, forexample, when the stimulus signal is delivered at a low current or lowvoltage, an EMG electrode picks up little or no EMG response, as shownin a first portion 24 of the trend 12. When the stimulus signal isincreased to a level that begins to activate innervated muscle, forexample, after level stimulus 18 in the graph 10, the muscle begins torespond and contract, and an increased EMG response is picked up by theelectrode. As the stimulus signal level continues to increase, thismuscle response increases as shown by the middle portion 22 of the trend12, denoting a zone where one or more muscles is actively contractingbecause of the applied stimulation. The monitored muscle has a maximumresponse level, for example a maximum possible contraction and EMGactivity at approximately amplitude 20 in graph 10. As the stimulusincreases beyond level 20, the innervated muscle reaches the maximumresponse and begins to plateau, as seen in the third portion 26 of thetrend 12. Also shown in FIG. 1 is point 16 on the curve 10. Point 16represents a point where the EMG response trend 12 transitions from theunresponsive portion 24 to the actively contracting zone 22, or thetransition from sub-threshold to above threshold EMG activity. Thistransition point is often sought during neuromonitoring. For example, todetermine the distance from a probe to a nerve or to evaluate theintegrity of a bone structure, it is often desirable to locate thestimulus level at or near the point where the EMG response trend 12transitions from portion 24 to portion 22. The stimulus at thistransition indicates the minimum stimulus level needed to elicit ameasurable response from the nerve and the innervated muscle. In orderto differentiate EMG signals from noise and determine the thresholdstimulus, an EMG threshold, such as threshold 14, can be applied to theEMG response profile in order to determine the stimulus signal level atwhich the trend 12 crosses the threshold 14. Various methods discussedbelow can be applied to determine or nearly estimate the stimulusrequired to reach point 16 and its corresponding EMG muscle response. Inorder to locate various points along the trend 12 for a given nerve andinnervated muscle, a neuromonitoring system can deliver a variety ofstimulus pulses at different levels and monitor responses from themuscle in order to analyze the health, proximity, or othercharacteristic of the nerve.

FIG. 2 shows components of a surgical neuromonitoring system accordingto certain embodiments. The surgical monitoring system 300 includes asurgical instrument 302 for delivering stimulation pulses. Thestimulating may be accomplished by applying any of a variety of suitablestimulus signals to an electrode or electrodes on the surgicalinstrument, including voltage and/or current pulses of varying magnitudeand/or frequency. Any suitable surgical instruments may be employed,including, but not limited to, any number of devices or components forcreating an operative corridor to a surgical target site (such asK-wires, sequentially dilating cannula systems, distractor systems,and/or retractor systems), devices or components for assessing pedicleintegrity (such as a pedicle testing probe), and/or devices orcomponents for retracting or otherwise protecting a nerve root before,during and/or after surgery (such as a nerve root retractor).

Measuring the response of nerves to the stimulation pulses may beperformed in any suitable manner, including but not limited to the useof compound muscle action potential (CMAP) monitoring techniques usingelectrodes 304 coupled to a patient (e.g., measuring the EMG responsesof muscle groups associated with a particular nerve). In certainembodiments, measuring the response of nerves is accomplished bymonitoring or measuring the EMG responses of the muscles innervated bythe stimulated nerves. The nerve detection module 306 and/or theprocessor 308 may digitize the signals and split the signal intocomponents communicated to a display instrument to provide a surgeon orother user with a visual display of the detected data.

A neuromonitoring system such as the system 300 shown in FIG. 2 deliversa plurality of stimulus signals, senses muscle responses to thestimulus, and processes the detected responses in order to identify EMGresponses, for example using the threshold determinations discussedbelow. This neuromonitoring process uses detection and processing of EMGresponses that are similar to typical EMG responses to stimulus signalsthat lie along the known response trend shown in FIG. 1. For example,the magnitude of an EMG response detected during surgery can be used tolocate the response long the typical trend in FIG. 1 and then assess thestimulated nerve based on the location of the response in the trend.FIG. 3 shows a graph 400 that depicts some illustrative EMG voltageresponses along the trend shown in FIG. 1 that may be elicited anddetected by a neuromonitoring system, such as the system 300. The trend422 in graph 400 shows the typical EMG response trend over a range ofstimulus levels. On the trend 422 are five stimulation points 402, 404,406, 408 and 410, along with their respective detected EMG responses414, 415, 416, 418 and 420. The responses 414, 415, 416, 418, and 420may be sensed, for example, by an EMG electrode, such as the electrodeshown in FIG. 2, when the respective stimulus signals are delivered. TheEMG response at point 404 falls below a threshold 412 along the trend422, while the EMG response at points 402, 406, 408 and 410 on/or fallabove the threshold 412. The EMG responses shown in windows 414, 415,416, 418 and 420 illustrate the corresponding change in the magnitudesof detected EMG responses as stimulus level is increased, and theresponses pass the EMG response threshold 412.

Starting below the threshold 412, when the stimulus is delivered atpoint 404, little or no EMG response is sensed by an electrode. As shownin window 415, there is no movement from the baseline of the sensed EMGsignal 429. The response processing employed detects little or nomovement from baseline in the signal 429, and indicates that thestimulus signal did not elicit an EMG response above the threshold 412.The next stimulation at point 402 falls right on the threshold 412, andthe corresponding response 430 in window 414 shows a small EMG response.The response 430 is a deviation having a standard EMG shape, with a lowresponse magnitude. Because point 402 lies on threshold 412, theprocessing system recognizes the peak 430 as a threshold EMG response.After the next stimulus at point 406, the response shown in window 416again has an appreciable deviation from baseline in a peak 424 detectedby an electrode. The peak 424 is a significant deviation from thebaseline, and follows the standard trend of an EMG signal.Post-processing of the signal in window 416 processes the peak 424 andidentifies the point 406 as a stimulus and EMG response falling abovethe cut-off threshold 412. As the stimulus level is increased to point408, the corresponding detected EMG response in window 418 alsoincreases. The response in window 418 exhibits a peak 426 deviating fromthe baseline EMG detection. The peak 426 has a sharper incline and ahigher peak deviation than the peak 424 detected at point 406. Thehigher peak 426 shown in window 418 is the result of a greater EMGresponse elicited from the monitored muscle by the stimulus delivered atpoint 408. Continuing further along the trend 422, the stimulusdelivered at point 410 elicits an even greater EMG response, shown bythe peak 428 in window 420. The peak 428 indicates an EMG response shownas a deviation from baseline typical of an EMG response, as the shape ofthe wave in window 420 mimics the waves shown in windows 416 and 418.The peak 428 has a higher deviation from baseline than both the peaks426 and 424 as a result of the EMG response elicited by the greaterstimulus level at point 410. Point 410 is located in the plateau regionof the trend 422, and thus further increases in the stimulus level, notshown in the graph 400, would be expected to elicit similar responses asthe response shown in window 420.

The EMG responses illustrated in windows 414, 415, 416, 418 and 420 inFIG. 3 show the difference between EMG responses below the threshold 412and at/or above the threshold level. In order to determine the preciselocation of the stimulation threshold 402, many conventional systemsapply techniques that require using multiple stimulations to locate anarrow estimate of the location of point 402. Not only can theseapproaches take a long time to converge on the accurate location (andthus provide feedback to the surgeon), they may endanger patient safetyby application of unnecessary stimulation signals. In addition, suchconventional systems are limited in their precision because thethreshold stimulation is necessarily a value at which an actualstimulation signal was applied. That is, conventional systems do notdisplay a calculated value as the stimulation threshold, but ratherrequire that the displayed stimulation threshold correspond to a valueapplied to tissue within the patient. Thus, to provide a precisionwithin 0.1 mA, for example, such conventional systems employ stimulationsignals at currents that are adjusted by increments of 0.1 mA until thethreshold is determined. According to an aspect of neuromonitoringdevice and methods described herein, the EMG response and associatedstimulus level that correspond to the threshold point 402 are estimatedfrom other stimulation and response information in the graph. Inparticular, in order to accurately estimate or determine the stimuluslevel corresponding to the point 402, a neuromonitoring system processesone or more of the EMG responses detected at other points in the trend422 that do not, preferably, correspond to the threshold itself When astimulus is delivered and an EMG response is detected, a standardpost-processing system is applied to analyze the detected signal todetermine where along the trend 422 the delivered stimulus point lies.In one implementation, the post-processing system determines first ifthere is an appreciable EMG signal, and second determines the magnitudeof the detected EMG response to determine where along the trend 422 thestimulus point lies.

In some implementations, this is done by applying a straight voltagethreshold to detected EMG signals in order to identify and evaluate themagnitude of potential EMG responses. Graph 500 shown in FIG. 4 depictstwo such thresholds applied to a detected EMG signal 502—an upper EMGresponse threshold 504 and a lower EMG response threshold 506. Those twothresholds can be selected by the operator or surgeon to set a preferredlevel of EMG sensitivity for the EMG detection module, or the thresholdsmay be standard thresholds set by the detection system. Also shown, thedetected signal 502 includes four peaks 508, 510, 512 and 514, which mayor may not be actual EMG responses to delivered stimulus signals. In thegraph 500, the thresholds 504 and 506 are applied to each of thepotential EMG peaks in order to determine both whether the peak is anactual EMG response or an artifact and also to evaluate the magnitude ofthe EMG response when an actual response is detected. At each peak, thesystem compares the EMG signal to the positive magnitude threshold 504and the negative magnitude threshold 506 and determines whether one orboth of the thresholds has been exceeded. If neither threshold isexceeded, the potential response is determined to be either too small tobe an appreciable EMG response or is determined to be artifact in thesignal 502 caused, for example, by noise in the detection system. Thus,the peak 508 is judged to be either an insignificant EMG response ornoise, as the peak 508 does not cross the threshold 504 or the threshold506. At peaks 510, 512 and 514, however, the signal 502 does exceed thethreshold 504 and the threshold 506, and these three peaks are judged assignificant EMG responses. For example, referring back to graph 400 inFIG. 3, the peak 508 may be judged as an EMG response at point 404,falling below the threshold 412 in graph 400, while the peaks 510, 512and 514 may be EMG responses elicited by stimulus signals at points 406,408 and 410 respectively, above the threshold 412 in graph 400.

In addition to determining whether or not the peaks in the signal 502are significant EMG responses, the neuromonitoring system processes eachdetected response to determine where along the typical EMG responsetrend, for example trend 422 in graph 400, each EMG response lies. Thisdetermination may be performed, for example, by determining the degreeto which each peak surpasses one of the thresholds 504 and 506. In FIG.4, the peaks 510, 512 and 514 each surpass the upper threshold 504 byincreasing amounts shown by offsets 516, 518 and 520, respectively. Theoffset 516 of the peak 510 from the threshold 504 is a relatively smalloffset and indicates that the peak 510, as well as its correspondingstimulus level, likely lies near the threshold in a typical EMG responsetrend, for example the trend shown in FIG. 1. The higher offset 518 ofpeak 512 and the higher offset 520 of peak 514 indicate that thestimulus level corresponding to those two peaks lie further along thetypical EMG response trend. Using this information, a processing systemcan take the four peaks 508, 510, 512 and 514, and their correspondingstimulus levels, and estimate where along a typical EMG response eachpeak and stimulus lies. The corresponding positions of the stimuluslevels that elicit the peaks can then be used in a determination ormodeling estimation approach to determine the minimum stimulus levelthat is required to produce an EMG response in signal 502 that peaksright at one of the thresholds 504 and 506.

An EMG signal threshold such as that depicted in graph 500 may besufficient for identifying when EMG responses are present in detectedEMG signals, but such approaches may also be vulnerable to inaccuraciesor false positives due to signal noise. For example, if a noiseinterruption is great enough, it may cause the baseline EMG signal toquickly jump either above an upper threshold or below a lower threshold,thus triggering a threshold detector to indicate an EMG response. Whilethe EMG signal may exceed one of the thresholds, the shape and patternof the signal may make it quite clear that the detected increase ordecrease from the baseline is simply noise and not an actual EMGresponse to a stimulus pulse. In the case of manual EMG review, aphysician would recognize that the quick sharp peaks caused by signalnoise do not look like an EMG response, and a physician viewing thesignals can dismiss such a signal as an insignificant deviation. Thestraight threshold detector, however, is not capable of making thiscomparison, and incorporating a check or an alternate trigger that isbased on the shape and orientation of the EMG signal may produce betterEMG response detection.

FIG. 5 shows an illustrative graph 600 that depicts a correlationapproach that uses the shape and pattern of a typical EMG response toimprove EMG detection and processing detected signals, thus providing amore robust detection mechanism. It is understood that while thecorrelation approach described below may reduce susceptibility to noiseand thus improve the reliability of the overall detection, the straightthreshold detector discussed above may be used where the signal-to-noiseratio is sufficiently low. Therefore, the methods and system disclosedherein are not limited to use of a correlation-based detector. Shown inthe graph 600 is a detected EMG signal 602 and a correlation signal 628produced by processing the EMG signal 602. In order to produce thecorrelation signal 628, the EMG signal 602 is processed by comparingportions of the signal 602 to a template 612 that is indicative of atypical size and shape of an EMG response. The template 612 shows an EMGsignal over a time window 614 that exhibits the expected EMG responseprofile from a muscle in which a contraction is triggered by a stimulussignal. In order to determine when EMG responses are present in thedetected signal 602, the template 612 is frequently, or continuously,compared to portions of the signal 602 to identify patterns in thesignal that match or closely mimic the template 612. A correlationfunction programmed into the processor compares the template 612 and theEMG signal 602. The correlation function shifts the template 612 tomultiple points along the time axis of the EMG signal 602 and performs amathematical calculation that compares the similarity of the template612 and the signal 602 over several pre-selected time windows along thegraph. For example, three template peaks 622, 624 and 626 are shown overthree time windows 616, 618 and 620 respectively. At each of these timewindows 616, 618 and 620, the correlation algorithm compares the shapeand magnitude of the corresponding template peak 622, 624 and 626 to acorresponding time window portion of the EMG signal 602. The output ofthe correlation function is a number that indicates the similaritybetween the respective template and the EMG signal 602 at a given timewindow.

The correlation signal 628 shows the results of comparing the template612 to the EMG signal 602 in a continuous manner along the time domainof EMG signal 602. The EMG signal 602 includes four peaks 604, 606, 608and 610 that may or may not be elicited EMG responses detected by an EMGelectrode. As the template 612 is shifted across the EMG signal 602, thesimilarity between the template 612 and each of the peaks 604, 606, 608and 610 results in corresponding peaks 630, 634, 638 and 642 in thecorrelation signal 628. Each of the correlation peaks 630, 634, 638 and642 indicates a period of similarity between the template 612 and theEMG signal 602. For example, the small correlation peak 630 correspondsto the similarity between the template 612 and the EMG signal 602 overthe time window 632, which is equal to the time window 614 of thetemplate 612. Likewise, each of the peaks 634, 638 and 642 correspond tothe similarity between the magnitude and trends of EMG signal 602 andthe template 612 detected over each of the time windows 636, 640 and644, respectively.

While each of the EMG signal peaks 604, 606, 608 and 610 bears somesimilarity to the template peak 612, not all the EMG signal peaks areactual EMG responses. For example, while the peak 604 is a deviationfrom the baseline of the EMG signal 602, it is only a minor deviationand does not have the pronounced shape and features of the template 612.Thus, the correlation peak 630 detected at the EMG signal peak 604 isminor, while the later peaks 634, 638 and 642 are more pronounced, astheir corresponding EMG peaks 606, 608 and 610 more closely mimic theshape and size of the EMG template 612. In order to differentiate thedeviations in EMG signal 602 that represent actual EMG responses andthose which are noise or minor deviations, a threshold 646 is applied tothe correlation signal 628.

The true neuromuscular responses in the EMG signal 602 are detected byidentifying the points at which the correlation signal 628 exceeds thethreshold 646. Similar to the EMG voltage threshold shown in graph 500,a deviation of the correlation 628 beyond the threshold 646 indicates afeature in the EMG signal 602 that should be considered a legitimate EMGresponse. As with the EMG threshold, the degree to which each identifiedpeak exceeds the threshold 646 can be used as an indicator of thelocation along the typical EMG response curve that each peak falls. Forexample, each of peaks 634, 638 and 642 exceeds the threshold 646, butthe three peaks exceed the threshold by differing degrees, increasingfrom offset 648 for peak 634 to offset 650 for peak 638 and offset 652for peak 642. Using these correlation peaks and their offsets above thethreshold 646, the processing system may place each of the EMG peaks606, 608 and 610, and the corresponding stimulus levels that elicitedeach of the peaks, along the typical EMG response curve in order tocalculate linear functions or other curve-fitting models for determiningthe minimum stimulus level required to elicit an EMG response. That is,the processor determines the minimum level required to produce a signalin the EMG signal 602 that leads to a correlation peak in thecorrelation signal 628 that rises just to the level of the threshold646.

This is done, for example, by applying a voltage threshold orcorrelating the EMG signal, and processing the signals and responses tolocate or estimate a minimum stimulus threshold. By relating detectedEMG responses to a typical EMG response profile, for example the EMGtrend shown in FIG. 1, the neuromonitoring system can reduce the numberof stimuli and responses, and thus the time required, to locate thethreshold within an acceptable resolution. Rather than continuouslyapplying varied stimulus until a very narrow range of stimuli isdetermined within which the threshold lies, the standard trend profilecan be applied to estimate the threshold stimulus level within anacceptable degree of accuracy. In some implementations, the trendprofile is determined by performing an initial test on the patient, orthe trend profile may be empirically determined.

FIG. 6 depicts an illustrative approach for delivering stimulus pulsesand calculating an estimated minimum threshold stimulus level based onneuromuscular responses elicited by the delivered stimulus pulses. Thecalculated threshold stimulation may be determined and communicated as acurrent, voltage, pulse width, charge or any other suitable stimuluslevel measurement. Graph 100 in FIG. 6 shows trend 102 in neuromuscularresponses, for example voltages measured by EMG electrodes placed in orover muscle tissue, versus the level of stimulus signals, for examplethe current, voltage, pulse width, or charge delivered from a stimulussource. Trend 102 follows the typical shape of EMG response in a muscleinnervated by a particular nerve when stimulus signals of increasingcurrent are delivered to an area proximal that nerve. As shown, thetrend 102 includes three portions: a first portion 128 over a range ofstimulus levels that do not elicit any appreciable or detectableresponse from the muscle tissue; a second portion 130 over which anincreasing EMG response is seen to the increasing stimulus levels; and athird portion 132 during which the EMG response levels off into aplateau over increasing stimulus levels. When a threshold level of EMGresponse, such as threshold 104, is applied to the trend 102, the point106 may be used for a nerve proximity calculation. Alternatively, thepoint 108 at the transition between portions 128 and 130 may be used.

In order to accurately estimate the stimulation threshold 112corresponding to point 106 or stimulus level 110 corresponding to point108, multiple stimulus signals and corresponding EMG responses may bedelivered and measured in order to locate a stimulus that produces anEMG response at or near the threshold point 106 or transition point 108of the trend 102. This approach, however, may require delivering a largenumber of stimuli to a patient. In order to improve the efficiency ofthe threshold detection system and to improve patient safety, fewerstimulations may be delivered, and the estimation shown in FIG. 6 can beapplied to estimate a point that is adequately close to the point 106 orpoint 108 for neuromonitoring purposes. In the example shown in graph100, no stimulation is actually delivered at stimulus levels 110 or 112.Rather, two stimulations, at levels 116 and 120, are delivered to apatient, and EMG responses are detected corresponding to eachstimulation signal. The detected EMG at point 114 for stimulus 116 andat point 118 for stimulus 120 provide enough data for the processingsystem to estimate the desired stimulation threshold. In certainimplementations, the system may use the threshold 104 to estimate point122 and stimulus level 124 as the threshold. In other implementations,the system may use the zero level of the EMG in portion 128 to estimatepoint 123 and stimulus level 125 as the threshold. The point 122 or 123may coincide precisely with the minimum threshold value 106 ortransition point 108, thereby providing the precise minimum stimulusthat corresponds to the stimulation threshold. However, such precisionmay not be necessary in all applications. Thus, in some implementations,the estimated threshold stimulation level 124 provided by point 122 or125 provided by point 123 is a short distance from the actual threshold112 and may be sufficiently accurate information to avoid nerve injury.In some implementations, a confirmatory electrical stimulation signalmay be delivered at the calculated threshold in order to confirm thecalculation, if desired.

Using the points 114 and 118, a slope is determined and a linearfunction model 126 is calculated. Using the linear model 126, theprocessing system can calculate the estimated threshold stimulus 124 atwhich the model 126 crosses the threshold 104, or can calculate thepoint 123 at which model 126 crosses the EMG zero level. Because the EMGtrend increases in a nearly linear manner in portion 130 of the trend,the model 126 provides an adequate estimator of the threshold stimulus112 whether point 122 or 123 is calculated.

In addition to points 114 and 118 used to create the linear model 126, athird stimulus point, for example point 108, can be factored in toimprove or verify the accuracy of the estimated threshold stimulus. Incertain embodiments, three points may be used to perform a linearregression, and can include calculating and reporting a reliabilityfactor that indicates the expected accuracy of the model. The linearregression may make use of two above-threshold points, such as points114 and 118, and one below-threshold point, such as 108, to include thedesired threshold within the range of detected EMG response points. Athird point may also be used to create additional linear models, forexample a linear model between point 108 and 114 or between point 108and 118, to calculate additional threshold estimations. The additionalestimations can be used to verify the precision of the linear models bydetecting whether the multiple estimations are clustered or spread overa wide range of stimulus levels.

In order to obtain the two EMG responses at points 114 and 118 afterdelivering respective stimulus signals at levels 116 and 120, multipleapproaches may be employed. For example, the delivered stimulus pulsesat levels 116 and 120 may be part of a sequence of stimulus pulses thatare delivered until two EMG responses are detected above the threshold104. A first stimulus may be delivered at stimulus level 110, and theEMG response may be detected at point 108 in trend 102. Theneuromonitoring system determines that the point 108 lies below thethreshold 104 and increases the level of the delivered stimulus to level116. When the EMG response to level 116 is detected at point 114, thestimulating and monitoring system can determine that the point 114 liesabove the threshold 104 and deliver a final stimulus at level 120 toobtain a second EMG response, at point 118, that is above the threshold104. Additional points may also be obtained along the curve bystimulating and monitoring the EMG response. The system then endsstimulus delivery and creates the model 126 using the two points 114 and118, which are above the threshold 104.

In other implementations, the first stimulus, for example at level 116,may be a set initial stimulus level that is delivered to the patient.When the stimulus 116 is delivered and the EMG response is measured atthe first stimulus point 114, the second stimulus level 120 may be setbased on the magnitude of the EMG response at the first stimulus point114. For example, when the point 114 lies within the second portion 130,the stimulating and monitoring system may slightly increase the stimulusto level 120 in order to obtain the second point 118. However, if thefirst stimulation fell below the threshold 104, for example atstimulation level 108, the neuromonitoring system may use a greaterincrease in stimulus in order to obtain a second point that would fallwithin the second portion 130 or the third portion 132. By contrast, ifthe first stimulation fell within the third portion 132 or towards theupper end of portion 130, the neuromonitoring system may decrease thestimulus level to obtain a second stimulation and response point fallingwithin either the first portion 128 or the second portion 130.

Once an initial determination of the stimulation threshold is made,subsequent determinations may start with stimulation levels that areselected in situ based on the prior value of the stimulation threshold.Stimulus levels may also be selected from a model of stimulus signalsand EMG responses for a particular nerve, or a general nerve stimulationmodel. In some implementations, the model used to select the stimulussignals may be specific to the nerve being monitored and may be createdfrom a series of test stimulus signals and detected test neuromuscularresponses. A series of stimulus signals having increasing levels, forexample increasing current, voltage, pulse width, charge, or acombination thereof, can be delivered at or near the modeled nerve, andEMG responses for each delivered stimulus can be recorded and plotted. Acurve or other model is then fit to the data, and the curve is used infurther modeling of the nerve to select the stimulus level or levelsfrom desired sections of the model, for example at or before the nearlylinearly increasing portion of the trend shown in FIG. 1 and discussedabove.

The model 126 uses two points, 114 and 118, that fall on the trend 102above the threshold 104 and within the second portion 130. Otherstimulation levels may be used that fall either outside of the secondportion 130 or that fall below the threshold 104 while still maintainingan adequate estimation of the stimulus 112 that produces the thresholdresponse at point 106 or stimulus 110 at transition point 108. Locatingthe stimulus 112 to a very precise degree often requires the delivery ofa large number of stimulations in order to narrow to a small range ofstimuli, from one stimulus that does not evoke an EMG response to asecond stimulus that does evoke the response. In the interest ofproviding a surgeon with a quick indication of nerve proximity or boneintegrity, the estimation approach may allow for a wider resolution inorder to reduce stimulations and increase speed. Thus, the smalldistance between the estimated stimuli 124 or 125 and the actualthresholds 112 or 110 may be an acceptable range, and the stimuli 124 or125 an adequate estimation for the purposes of neuromonitoring duringsurgery.

FIG. 7 shows a graph 140 that illustrates an estimation approach thatutilizes a first EMG response at point 142, below the threshold 104, anda second EMG response at point 146 that lies above the threshold 104 toobtain an estimate of the threshold stimulus 112 or 110 that producesthe threshold response at point 106 or 108 along the trend 102. As shownin the graph 140, the linear function model 154 is created bycalculating a slope between the point 146 and the point 142. The model154 can be used to provide an adequate estimated stimulation threshold152 that would produce a threshold response at point 150 along the model154 or can be used to estimate a threshold stimulus 144 where model 154crosses the EMG zero, at /or near point 142. Although the point 142,corresponding to the first delivered stimulus level 144, falls below thethreshold 104, an acceptable estimated threshold stimulus level 152 or144 can still be calculated. Thus, when stimulation is delivered at twolevels 144 and 148 that do not both produce EMG responses that lie onthe nearly linear portion of the trend 102, the linear estimating model154 can still be sufficient to provide an estimated stimulationthreshold while requiring only two stimulation signals to be deliveredto a patient. In some implementations, the calculation may use threestimulation signals and three neuromuscular responses—one stimulationsignal that does not produce an above-threshold response and twostimulation signals that produce above-threshold responses in the nearlylinear portion of the trend curve.

FIG. 8 shows a graph 160 illustrating an estimation approach that uses afirst EMG response at point 162 in the nearly linear portion of thetrend 102 and a second EMG response at point 166 in the plateau regionof the trend 102. The point 162 corresponds to a delivered stimuluslevel 164, while the point 166 corresponds to a delivered stimulus level168. From the two EMG responses at points 162 and 166, a slope iscalculated, similar to the approaches in FIGS. 6 and 7, and a linearfunction model 174 is used to approximate the trend 102. From the model174, the threshold stimulus level 112 can be estimated as level 172producing the EMG response at point 170 on the model 174 or can beestimated as level 175 producing an EMG response at point 173 at thezero EMG level of model 174.

While linear estimation approaches such as those shown in the FIG. 6-8may provide accurate estimations of threshold stimulus levels, otherapproaches may use the generally known sigmoidal shape of the typicaltrend 102 to apply a curve-fitting approach that may produce moreaccurate estimations, particularly more accurate estimations over awider range of delivered stimulus levels. Graph 200 in FIG. 9 shows anexample of a curve-fitting estimation approach using more than twostimulations. In this approach, four stimulation signals are deliveredat levels 202, 204, 206 and 208. The delivered stimuli elicit four EMGresponses detected at points 212, 214, 216 and 218. As shown in thegraph 200, the first point 212 falls below the threshold 224 while theother three points 214, 216 and 218 fall above the threshold 224. Thisindicates that the desired threshold stimulus level falls somewherebetween the delivered stimuli at 202 and 204.

In order to estimate the minimum threshold stimulus, the four detectedEMG responses 212, 214, 216 and 218 are input into a sigmoid functionmodeling process that uses the four detected responses to estimate amodel 222 that mimics the known typical EMG response pattern. From themodel 222, an estimated minimum threshold stimulus level 210 can becalculated from the point 220 that falls on the threshold 224 in themodel 222. The curve-fitting approach may thus provide estimations ofthe minimum threshold while still limiting the number of deliveredstimulations that measure EMG responses to as few as three or fourstimulations.

In order to create the curve fit model 222 shown in FIG. 9 to assessbaseline excitability for a particular nerve or to select future testingstimulus levels, data for a series of pulses and corresponding EMGresponses is obtained for the nerve. FIG. 10 shows a sequence ofstimulus signals in graph 700 and corresponding EMG responses in graph750. In particular, FIG. 10 shows eight pulses 702-709 and theirrespective EMG responses 752-759. The stimulus level of each of thepulses 702-709 is increased relative to the previous pulse. Inparticular, the level of each subsequent pulse is increased by aconstant increment 762, shown between pulses 702 and 703. The increasemay be the result of adjusting current, voltage, pulse width. charge,pulse shape, any other suitable characteristic, or a combinationthereof. As a result of the increased level of each successive stimuluspulse, the magnitude of the sensed EMG responses in graph 750 increaseswith each subsequent pulse. For example, responses 752 and 753 showlittle, if any, deviation from the EMG base line in response to pulses702 to 703, while pulses 758 and 759 show large deviations from the EMGbaseline in response to the larger pulses 708 and 709.

The pulses and responses shown in graphs 700 and 750 depict astimulation and monitoring approach useful for measuring one or moreresponses that may be plugged into the extrapolation or estimationtechnique discussed above with respect to FIGS. 6-9. For example, thetrain of pulses shown in graph 700 may continue with constant increment762 between each pulse until two EMG thresholds are detected in graph750. Once the two pulses above the threshold are detected, the systemcan stop delivering the stimulation pulses and use the last twoabove-threshold EMG responses and the corresponding stimulus levels touse as input to the estimation or curve-fitting calculations used toestimate the threshold stimulus. The stimulus train shown in graph 700may start at a low level, as shown for pulse 702, and increase until thetwo above-threshold responses are detected, or may start at a higherlevel that is known to be at or near the threshold level.

The pulses delivered in graph 700 not only increase in level by theincrement 762, but are temporally spaced apart by a constant time period764. The period 764 between each pulse is set such that the muscleinnervated by the monitored nerve may recover after a contraction or EMGresponse. The time period 764 can be set such that it is greater than orequal to the known refractory period of the monitored nerve and theinnervated muscle. For example, the time period 764 is set to be greaterthan the amount of time that a muscle is known to have a refractoryperiod during which it recovers before another full stimulation andresponse is possible. In addition, the time period 764 can take intoaccount the signal transit time that is required for a nerve signal totravel from the point of stimulation to the innervated muscle beforecontraction begins. This signal transit time is shown by time period 760between the beginning of the pulse 704 and the beginning of the sensedEMG response 754 corresponding to that pulse. In addition to taking intoaccount the time that the neuron stimulated by pulse 704 and the muscleresponding at peak 754 need in order to recover from the stimulus, thetime period 764 can also take into account the time period 760 requiredfor the transit of the stimulation signal from nerve to muscle.

The transit period 760 may also be used to time EMG monitoring andeliminate noise from the sensed EMG signal shown in graph 750. Forexample, the known signal transit delay between stimulus pulse and EMGresponse can be used to create predetermined monitoring windows duringwhich the system monitors for EMG responses, as shown in graphs 770 and780 in FIG. 11. Graph 770 shows a series of three stimulus pulses 772,774 and 776, while graph 780 shows a series of corresponding EMGresponses 782, 784 and 786. Each of the EMG responses is offset from itscorresponding stimulus pulse by a time period. For example, the EMGresponse 782 trails its corresponding stimulus signal 772 by a timeperiod 790. As discussed above, this time period 790 arises due to thetransit time required for the stimulus signal to travel from the pointof stimulation to the innervated muscle and for the innervated muscle tobegin the contraction that produces the EMG response 782.

The transit time period 790 is generally known for a given pair of nerveand innervated muscle. This known time value can improve the EMGmonitoring used to produce the graph 780 by only detecting or analyzingresponses in a time window during which EMG responses are expected. Forexample, a sensing module is configured to apply a sensing window 794 toan EMG response curve indicative of the time window in which an EMGresponse is expected. After a stimulus pulse 774, the neuromonitoringsystem ignores EMG signals outside of the sensing window 794. Thesensing window 794 is a period of time that is predetermined and isoffset from its corresponding stimulation pulse 774 by a time period 791that is shorter than period 790, the known transit time between thenerve and the muscle. The window 794 is created by starting the window794 at the time period 791, at the left boundary 793 of the window. Thewindow 794 then continues for the set time width of the window, endingat right boundary 795. By detecting and analyzing only EMG signalsreceived within the sensing window 794, the system may cut out any noisedetected before the left boundary 793 of the sensing window 794 or afterthe right boundary 795 of the sensing window 794. This eliminates thepossibility of detecting any false positives caused by noise outside ofthe sensing window 794 during which the true EMG response occurs.Likewise, a predetermined sensing window 796 may be set in response tothe stimulation signal 776. Like the sensing window 794, the sensingwindow 796 is offset from the stimulation pulse 776 by the time period791 and has a width that is equal to the sensing window 794. Programmingthe system to use this window can eliminate false positives from noisedetected outside of the sensing window 796 and help identify the trueEMG response 786 in response to the stimulation 776.

In addition to using the known transit time between nerve and muscle tocut out noise outside of sensed EMG windows, the transit time may alsobe used to decrease the amount of time required for the delivery ofsequential stimulation pulses and the detection of subsequent EMGresponses. While FIG. 11 shows a sequence in which a single pulse 772 isdelivered followed by detection of an EMG response 782 before the nextstimulation pulse 774 is delivered, the use of time windows may compressthe stimulation signals shown in graph 770 such that two or morestimulation signals may be delivered before any EMG response is detectedin response to the first stimulation. The known transit time betweeneach stimulation and EMG response is then used to relate each sensed EMGresponse to its corresponding stimulation pulse, as shown in FIG. 12.

Graph 800 shows three stimulation pulses 802, 804 and 806, each of whichis delivered before any EMG response is detected in the correspondingEMG response graph 850. As shown, each of the three stimulus signals802, 804 and 806 is delivered before the first EMG response 852 isdetected in response to the stimulus signal 802. The time period 860shown in FIG. 12 between the beginning of the stimulus pulse 802 and thecorresponding EMG response 852 is long enough that the three stimulationpulses can be delivered within the time 860 while still allowing boththe nerve and innervated muscle to recover from each subsequent pulse.The time period 862 between each stimulus pulse, for example betweenpulse 802 and 804, is set so that the time between the pulses is atleast as long as the refractory period of the nerve and muscle. Afterthe three pulses 802, 804 and 806 are delivered, a sensing module maydetect EMG responses during a sensing window 864 that starts at timeperiod 860, before the time of the expected EMG response for the pulse802 and ends after the expected time of the corresponding EMG responsefor pulse 806. Within the sensing window 864 in which the threeresponses 852, 854 and 856 are detected, each individual response isrelated to its corresponding stimulus pulse by using the known transittime between the monitored nerve and muscle. The delivery of pulses andsensed EMG responses shown in graphs 800 and 850 can be compressed intime relative to the stimulus pulses and EMG responses shown in graphs770 and 780 of FIG. 11. This approach eliminates the need to wait thefull signal transit time after each pulse before delivering a nextpulse, and thus may allow for quicker and more efficient localizationand distance calculations in neural monitoring.

The approaches discussed above utilize increasing levels of stimulussignals in order to detect and locate multiple points along an EMGresponse curve, for example the typical response curve shown in FIG. 1.In addition to (or in lieu of) the current of a stimulus signal, otherstimulus characteristics, for example voltage or pulse width, may beused to produce the different stimulus levels and locate various pointsalong the EMG response trend and determine stimulation characteristicsthat may be used to guide a surgical tool. FIG. 13 shows examples ofusing varying current and varying pulse width to produce aneuromonitoring approach similar to the monitoring and detectionapproaches discussed above. In a first graph 900, three stimulus pulses908, 910 and 912 are shown with a constant pulse width but varyingcurrent, while graph 920 shows three stimulus pulses 928, 930 and 932that are delivered at constant current but varying pulse width. In graph900, the level of each successive stimulus signal increases as thecurrent is increased by a constant increment 914 between each pulse. Forexample, stimulus 908 is delivered at a current 902 while the nextstimulus 910 is delivered at a higher current 904, and finally stimulus912 is delivered at the higher current 906. Each of the stimulus pulses908, 910 and 912 has the same pulse width 916, and thus the increasingcurrent from 908 to pulse 912 increases the amount of charge deliveredfor each subsequent stimulus pulse. Graph 920, on the other hand,depicts the three stimulus pulses 912, 930 and 932 delivered at a singleconstant current 922 that does not increase from pulse to pulse. Thepulse widths of the pulses 928, 930 and 932, however, do increase foreach subsequent pulse, from the pulse width 934 for stimulus 928 to thepulse width 936 for pulse 930 and finally the pulse width 938 forstimulus 932.

Both the increasing current in the pulses of graph 900 and theincreasing pulse width of the pulses in graph 920 provide a largerstimulus (or higher total coulombs) to the nerve for each subsequentdelivered pulse. Though the pulse width does not change in graph 900 andthe current does not change in graph 920, each of the three pulses shownin each graph may elicit increasing responses in an innervated muscle asa result of the charge delivered to the tissue. For example, stimulus908 has a total charge that is depicted by the area 909 of the pulse,while the stimulus 928 has a corresponding area 929 that depicts thequantitative amount of charge delivered during that pulse. Because thepulses 908 and 928 are delivered at substantially the same currents 902and 922 and have substantially the same pulse width 916 and 934, thesepulses are essentially equivalent and would elicit the same response inan innervated muscle. The second pulses 910 and 930 have differingshapes, however, they deliver a similar cumulative amount of charge tothe nerve during the pulses, as the area 911 of pulse 910 is and thearea 931 of the pulse 930 are similar. In pulse 910, the current of thepulse is approximately doubled relative to the pulse 908, and thus thearea 911 is double the area of 909 of stimulus 908 and the amount ofcharge delivered by stimulus 910 is doubled. For stimulus 930, thecurrent 922 is the same as the pulse 928, but the pulse width 936 isdouble the pulse width 934 of the stimulus 928. Thus, the charge, orarea 931 of the stimulus 930, is approximately doubled relative to thestimulus 928. As a result, the pulses 910 and 930 deliver charges to anerve and that would both elicit a response from the innervated muscle.Finally, the pulse 912 is increased again by the current increment 914relative to stimulus 910 and has a level that is three times the levelof the first pulse 908, an increase by 50% over the stimulus 910. Thisresults in an area 913 of the pulse 912 that is approximately threetimes the area of the original pulse 908. Likewise, in graph 920, thepulse 932 has a pulse width 938 that is three times the original pulsewidth 934 and 50% larger than the pulse width 936. The resulting area933, or the quantitative charge delivered by the pulse 932, isapproximately three times that of the original pulse 928. Thus, thepulses 932 and 912 would also be expected to elicit EMG responses fromthe innervated muscle.

The varying pulse width approach shown in FIG. 13 may be used tonavigate the typical EMG response curve shown in FIG. 1 and locatemultiple points along the curve that can be used to determine orestimate a threshold stimulation. The varying pulse width approach canbe used if a constant current, for example current 922 shown in FIG. 13,is desired for stimulus pulses rather than an increasing current thatmay reach levels that can cause discomfort for a patient. Constantcurrent is not required, and pulse width may be varied along withcurrent, but may be preferred to keep current at a known constant fordelivered stimulations. In addition, lower current can be used in avarying pulse width approach to reduce a power demand on a system, whichmay be useful in decreasing energy demands of a neuromonitoring device,particularly in the case of battery-powered devices. For battery poweredor wireless stimulus devices, the reduction in power consumptionprovided by the varying pulse width can provide for a longer device lifeor longer battery life between charges.

Stimulation signals allow an operator to control multiplecharacteristics of stimulus pulses to control the level of stimulusdelivered to a patient. For example, the voltage, current, pulse width,charge, shape, or other characteristic of a pulse can be programmed fora particular application in order to achieve the desired stimulus level.Changes in one or more of these characteristics can increase thestimulus level and adjust stimulus signals to identify a combination ofthe stimulus characteristics that stimulates a nerve. An example showingthe effect of changing one of multiple characteristics can be shown bythe relationship between a signal strength, for example currentamplitude or voltage, and signal duration, for example pulse width.

The relationship between stimulus strength, for example currentamplitude or voltage, and stimulus duration, for example pulse width, isshown as one example of adjusting multiple stimulus characteristics in athreshold curve for a given nerve, for example the curve 952 shown inthe graph 950 of FIG. 14. Curve 952 depicts the relation betweenstimulus strength and duration required for stimulation of a particularnerve. The curve for a particular nerve varies from nerve to nerve basedon the excitability of the nerve. The curve 952 depicts the minimumproportion between stimulus level and duration of stimulus pulse thatwill cause stimulation of a nerve and contraction of a muscle innervatedby the nerve. For example, a stimulus pulse delivered with a pulse width958 and a level at point 954 lies below the curve 952 and thus would notcause stimulation of the nerve depicted by the curve. If the stimuluspulse was increased up to point 956 but remained at pulse width 958, theresulting stimulus would cause stimulation of the nerve andcorresponding muscle, as point 956 lies above the curve 952. The secondcurve 953 in graph 950 depicts a second nerve that is less excitablethan the nerve depicted by curve 952, and the second nerve 953 stillwould not be stimulated by the pulse delivered at point 956, as thatpoint lies below the curve 953. If, however, the stimulus level wasagain increased to point 960, that point lies above both curves 952 and953, and thus a pulse delivered at point 960 having the pulse width 958would stimulate either of the nerves shown by the two curves.

With respect to pulse width variation, the stimulus delivered at point962 in the graph 950 at level 966 would not stimulate the nerve becausethat point lies below the curve 952. If, however, the pulse width wasincreased to point 964, the stimulus delivered at 964 would stimulatethe nerve and muscle, as that point now lies above the curve 952. Thecharge delivered at each of points 962 and 964 is depicted by areas 963and 965, respectively. This area under the curve shows a quantitativeamount of charge at point 964 that is larger than the charge at point962. The charge shown by area 963 is not sufficient to stimulate thenerve, while the larger charge at point 964 is sufficient and triggersthe nerve. Thus, by varying at least one of stimulus level and duration,a neuromonitoring system can be employed to find at least one point thatlies below the curve and one point that lies above the curve either atconstant voltage, constant current or constant pulse width.

The EMG responses detected by varying pulse widths of stimuli held at aconstant current is shown in the graphs 1000 and 1050 in FIG. 15. Threestimulus pulses 1002, 1004 and 1006 are delivered to a nerve at aconstant level 1008. In response to the stimulus pulses, three EMGresponses 1052, 1054 and 1056 are detected in a muscle innervated by thestimulated nerve. As shown, the magnitude of each successive EMGresponse increases as the pulse width of each stimulus pulse increases,from a width 1001 for pulse 1002 to a width 1003 for pulse 1004 and awidth 1005 for pulse 1006. The increase in pulse width at constant levelcreates a larger charge delivered to the nerve for each successivepulse, and thus the magnitude of EMG responses increases from response1052 to responses 1054 and 1056. The pulse width of successive stimulimay be increased until a EMG response greater than or equal to an EMGthreshold is detected. The threshold, for example threshold 1058, may beapplied to the EMG detected signal to determine whether a thresholdresponse is present, as discussed above. As shown in graph 1050, pulses1002 and 1004 elicit below-threshold responses 1052 and 1054 while athird pulse 1006 elicits an above-threshold response 1056 from themuscle. Using this increasing pulse width approach, a neuromonitoringsystem is able to determine pulse widths both below and above thedesired EMG threshold, for example pulse widths 1001 and 1003 below thethreshold and pulse width 1005 above the threshold for the constantlevel 1008.

The above-threshold pulse width 1006 determined in FIG. 15 may bereported, or may be used to calculate the total charge in coulombsrequired to elicit the above-threshold response. As an alternative, thepulse width may also be plugged into an estimation calculator, such asthe extrapolation and estimation or curve-fitting approaches discussedabove, in order to estimate the minimum pulse width required to elicit athreshold response without actually delivering any stimuli at thecalculated pulse width. While the stimuli and corresponding responsesshown in FIG. 15 alternate between stimulus and EMG detection, multiplepulses may be delivered before any EMG response is detected, asdiscussed above with respect to increasing current pulses in FIG. 12.For example, depending on the width of each pulse and the delay betweena pulse and the corresponding muscle reaction, the three stimulus pulses1002, 1004, and 1006 may be delivered before the first EMG response 1052is detected.

EMG responses and corresponding stimulus pulse widths can be used todetermine an estimate of the minimum stimulus level. For example interms of pulse width for a given constant current, required to elicit athreshold neuromuscular response from the monitored nerve and musclepair. The increasing pulse width stimuli and corresponding EMG responsescan be located along the EMG response curve shown in FIG. 1 and used tocreate linear or curve fit models to calculate an estimated minimumpulse stimulus strength, in terms of pulse width, as discussed abovewith respect to FIGS. 6-9. In other implementations, rather thanmodeling and estimating the threshold, a neuromonitoring system mayapply additional stimuli at additional pulse widths to narrow a rangewithin which the minimum threshold may lie until a range having a widthless than or equal to a desired resolution is determined. This approachis illustrated in FIGS. 16-19.

In FIG. 16, a sequence of stimulus signals having increasing pulsewidths is shown in graph 1100, and corresponding detected EMG responsesto the delivered stimuli are shown in graph 1120. The first stimulus1102, having a pulse width X, delivered in the vicinity of a nerveresults in a detected EMG response 1122 trailing the stimulus. Aneuromonitoring system applies an upper EMG threshold 1130 and a lowerEMG threshold 1132 defining deviations from the EMG baseline 1134 thatare great enough for EMG signals to be considered true EMG responses,and the system determines whether the response 1122 is greater than orequal to either of the thresholds. Certain neuromonitoring systems andmethods may use correlation, for example the correlation approachdiscussed above with respect to FIG. 5, rather than EMG signal voltageto differentiate above-threshold and below-threshold EMG responses. Whenthe system determines that response 1122 is does not meet either of thethresholds 1130 and 1132, a second stimulus 1104 is applied having apulse larger than the pulse width of stimulus 1102.

The pulse width of the second stimulus 1104 is increased by an incrementX, resulting in a pulse width of 2X for the stimulus. The larger pulsewidth delivers more charge in the vicinity of the monitored nerve, andthus is expected to elicit a greater EMG response from the monitoredmuscle. This is shown in graph 1120 by the response 1124, which trailsthe stimulus 1104 and deviates from the EMG baseline 1134 to a largerdegree than the previous response 1122. The response 1124, however, doesnot meet either of the threshold 1130 or 1132, so a third stimulus 1106is scheduled. The stimulus 1106 has a pulse width that is increased by Xrelative to the pulse width of stimulus 1104, making the pulse width ofstimulus 1106 3X. A response 1126, which is larger than the responses1122 and 1124, is then detected, but does not meet either of thethresholds 1130 or 1132. A fourth stimulus 1108 having a pulse widthincreased by X relative to stimulus 1106 to 4X is then delivered, and afourth response 1128 is detected in response to the stimulus. Followingthe fourth response 1128, the neuromonitoring system is able todetermine that the pulse width of stimulus 1108 has elicited a thresholdEMG response 1128 from the monitored muscle, and thus the pulse width ofstimulus 1108 is either greater than or equal to the pulse widthrequired to elicit a response that equals the threshold.

Stimulus 1106, having a pulse width of 3X, elicits a response 1126 thatdoes not exceed the thresholds 1130 and 1132, while stimulus 1108,having a pulse width of 4X, elicits a response 1128 that exceeds thethresholds 1130 and 1132. Thus, the minimum pulse width required toelicit a threshold EMG response falls within the range of pulse widthsgreater than 3X and less than or equal to 4X. In some implementations,the desired resolution may be greater than the range 3X-4X, and theneuromonitoring system may output 4X as the estimated stimulationthreshold pulse width. In other implementations, however, the desiredresolution may be less than the range 3X-4X, and further stimulation andmonitoring is needed to narrow this range. In such cases, theneuromonitoring system may deliver further stimulus signals having pulsewidths between 3X and 4X and determine which signals elicit thresholdresponses until a smaller range having a lower bound that does notelicit a threshold response and an upper bound that does elicit athreshold response is determined and is smaller than the desiredresolution. FIGS. 17-19 depict three illustrative approaches fornarrowing the 3X-4X pulse width window until it is within a desiredresolution of 0.25X, smaller than the 1S initial pulse width range from3X-4X.

FIG. 17 shows a graph 1140 of stimulus signals and a graph 1150 ofcorresponding EMG responses used to narrow the 3X-4X pulse width rangeuntil it is less than or equal to the desired 0.25X resolution.Following the pulse 1108 and corresponding response 1128, theneuromonitoring system delivers a stimulus 1142 at a pulse width of3.5X, cutting the 3X-4X range in half. If a threshold EMG response isdetected following the stimulus 1142, then the desired minimum pulsewidth is determined to lie within the narrower range 3X-3.5X, while alack of an EMG response following the stimulus 1142 narrows the range to3.5X-4X. The detected response 1152 following the stimulus 1142 exceedsthe thresholds 1130 and 1132, and thus the range containing the minimumthreshold is narrowed to 3X-3.5X. The neuromonitoring system again cutsthis range in half, and a following stimulus 1144 having a pulse widthof 3.25X is delivered. The EMG response 1154 then determines the finalrange containing the minimum threshold, as a threshold EMG responsenarrows the range to 3X-3.25X, and lack of a threshold EMG responsenarrows the range to 3.25X-3.5X. Both of these ranges are equal to thedesired threshold, and thus the neuromonitoring system communicates athreshold of 3.25X if the EMG response exceeds the EMG thresholds 1130and 1132 or communicates a threshold of 3.5X if the EMG response doesnot exceed the EMG thresholds. As shown in graph 1150, the response 1154exceeds the EMG thresholds 1130 and 1132, and thus the neuromonitoringsystem reports a determined minimum threshold pulse width of 3.25X.

Rather than cutting the 3X-4X pulse width range in half, sometimesreferred to as bisection, until a suitable range is determined, aneuromonitoring system may deliver stimuli within the range thatdecrease or increase by an amount equal to the desired resolution untila range is determined that is equal to the resolution, has a lower boundthat does not elicit a threshold EMG response, and has an upper boundthat elicits a threshold EMG response. FIG. 18 shows a narrowingapproach that begins with the 4X stimulus 1108 in graph 1160, whichelicits the threshold EMG response 1128 in graph 1170, and decreases thestimulus pulse width by 0.25X, the desired resolution, until a finalrange is determined. After the stimulus 1108, the pulse width of thenext stimulus 1162 is decreased by 0.25X to 3.75X. A subsequent response1172 meets the EMG thresholds 1130 and 1132, and the range of pulsewidths containing the minimum threshold is narrowed to 3X-3.75X, whichis still larger than the 0.25X resolution. The next stimulus 1164 has apulse width that is again decreased by the 0.25X decrement to 3.5X, andthe resulting response 1174 again exceeds the thresholds 1130 and 1132.

Following the stimulus 1164, stimulus 1166 is delivered having a pulsewidth of 3.25X. The stimulus 1166 is the last stimulus needed to narrowthe range containing the threshold to a width of 0.25X, and thus amaximum of three subsequent pulses is required to narrow the range tothe desired resolution after the threshold EMG response 1128 isdetected. As shown in graph 1170, the subsequent response 1176 exceedsthe thresholds 1130 and 1132, and thus the neuromonitoring systemreports 3.25X as the determined minimum pulse width threshold.

While FIG. 18 illustrates an approach that begins at the upper bound ofthe initial pulse width range and decreases by an amount equal to thedesired resolution, the final range can also be determined by startingat the lower bound of the initial range. This approach is shown in FIG.19, which depicts stimulus signals in graph 1180 and corresponding EMGresponses in graph 1190. After the stimulus 1108 and threshold EMGresponse 1128, the neuromonitoring system begins at the lower bound ofthe initial range, 3X, and increments by the resolution, 0.25X,delivering a stimulus 1182 having a pulse width of 3.25X. The resultingEMG response 1192 exceeds the threshold 1130 and 1132, and thus thepulse width range of 3X-3.25X is determined to include the minimumthreshold pulse width range. As a result, a minimum of one subsequentstimulus pulse may result in determining the threshold within anacceptable resolution in either the decrementing approach of FIG. 18 orincrementing approach of FIG. 19. If however, the response to stimulus1182 was not a threshold EMG response, subsequent stimuli 1184 and 1186are delivered having pulse widths of 3.5X and 3.75X until a thresholdEMG response is detected, and the stimulus eliciting that response isreported as the minimum threshold. If no threshold EMG response has beendetected following the 3.75X stimulus, the neuromonitoring systemreports 4X as the minimum threshold pulse width.

During neuromonitoring, determined thresholds and underlying EMG andstimulus data are continuously presented to a Surgeon. The displays usedcan provide a customizable interface for a Surgeon or other Professionalto control the displayed data. Illustrative examples of such displaysare shown in FIGS. 20-34.

FIG. 20 shows a surgical monitoring system 2010 according to certainembodiments. The surgical monitoring system 2010 includes a displaydevice 2012 having a monitor or display 2014 and a user interface 2016for receiving user commands, although in certain embodiments the display2014 includes a touch-screen interface for receiving user inputs. Thedisplay device 2012 is communicatively coupled to a second displaydevice 2022 using a data link 2020 that may be a physical connection ora wireless connection. For example, the display devices 2012, 2022 maybe connected to each other by a communication medium, such as a USBport, serial port cable, a coaxial cable, an Ethernet type cable, atelephone line, a radio frequency transceiver or other similar wirelessor wired medium or combination of the foregoing. The communicationbetween the display devices 2012, 2022, and any of the other componentsin FIG. 20, can follow various known communication protocols, such asTCP/IP, cellular protocols including GSM, Wi-Fi, Wi-Max, or otherwireless communications technologies or combination of wired or wirelesschannels. The second display device 2022 includes a monitor or display2024 that may be configured with a touch-screen interface for receivinguser inputs or, alternatively or additionally, may be provided with auser interface similar to the user interface 2016 shown for the firstdisplay device 2012. In certain embodiments, the display 2024 of thesecond display device 2022 need not include a user input interface.

The display device 2012 is coupled to a base unit 2030, and one or moreof a remote amplifier 2032, 16-channel external amplifier 2034, andstimulator splitter 2036 (e.g., a EX-IX stimulator) for measuring anddisplaying the electrical signals generated by muscles, the centralnervous system, and/or the peripheral nerves.

FIG. 21 shows an illustrative display screen 2050 according to certainembodiments. As discussed above, certain display screens can beintegrated to include both the monitorist views and the surgeon views.The display screen 2050 includes various windows that displayphysiological data for a patient according to different modes, includinga surgeon window 2060, technician or monitorist window 2070, and rightand left EMG windows 2080, and further includes an event timeline 2090along the bottom of the screen. The event timeline 2090 includes a rightand left arrow 2092 for moving between each of the events 2094 along thetimeline. Each of the windows 2060, 2070, 2080 has a window title bar2062, 2072, 2082 across the top of the respective window that allows thewindows to be docked and undocked from the display screen 2050 andplaced in any position on a monitor controlled by the monitoring system2010. For example, docking and undocking the surgeon window 2060 allowsthat window to be displayed for the surgeon on a separate monitor suchas that provided by the second display device 2022 of FIG. 20. Thewindows may be undocked by grabbing the window title bar using a cursorcontrolled by a mouse or other input device, including user touch-screencommands, and then moving the window to any position on a monitorcontrolled by the monitoring system 2010.

In certain embodiments, to dock an undocked window into a particularregion on the display screen, a docking tool is provided that includes aset of arrows that appear when the title bar for that window is selectedwith the cursor. The potential docking regions for that window will beshadowed in the display screen, and hovering the cursor over differentarrows of the docking tool allows the user to see the different dockingregions that are available. When a desired docking location isidentified, the user releases the title bar and the window becomesdocked at the desired docking position. For example, as shown in FIG.22, a display screen 2100 includes a left region 2102 and blank rightregion 2104 into which the mode window 2110 may be docked. When thecursor is positioned over the right arrow of the docking tool 2101 andthe window title bar 2112 is released, the mode window 2110 is dockedinto the right region 2104 of the display screen 2100. Similarly, asshown in FIG. 23, a display screen 2120 includes a bottom region 2122and a blank top region 2124 into which the mode window 2130 may bedocked. When the cursor is positioned over the top arrow of the dockingtool 2121 and the window title bar 2132 is released, the mode window2130 is docked into the top region 2124 of the display screen 2120. Asshown in FIG. 24, a mode window can be docked along the top of a displayscreen 2140 having multiple windows. The display screen 2140 includesleft and right bottom regions 2142, 2144 and a blank top region 2146into which the mode window 2150 may be docked. When the cursor ispositioned over the top arrow of the docking tool 2141 and the windowtitle bar 2152 is released, the mode window 2150 is docked into the topregion 2146 of the display screen 2140.

As discussed above, the surgical monitoring system allows forsimultaneous surgeon and monitorist views of data that is recorded by anerve detection algorithm. In certain embodiments, this dual-viewfeature can be implemented by undocking the surgeon window 2060 from theintegrated view of display screen 2050 of FIG. 21 and placing thesurgeon window 2060 into a second, surgeon-facing, monitor on the seconddisplay device 2022. It will be understood that any suitable techniquemay be used to cause the first and second display devices 2012, 2022 todisplay the surgeon and monitorist views and that docking and undockingthe windows is merely exemplary. In particular, any technique formodifying or otherwise customizing the displays to provide different butsimultaneous presentation of a neuromuscular response on differentscreens may be used. In certain embodiments, the nature of theinformation displayed in the two (or more) displays depends on auser-selected indication (or automatically determined designation) ofthe type of user (e.g., monitorist or surgeon).

The surgeon view displays information in a relatively simple andeasy-to-read manner. For example, as discussed above, the monitoristview may include the waveform responses to the current stimulus whilethe surgeon view does not; instead including numeric and/or graphicalindicators of distance and or current amplitude based on the samewaveform responses. In certain embodiments, the surgeon view 2200displays information to the surgeon in two respects.

First, as shown in FIG. 25, the surgeon view includes a dial 2201 thatindicates the lowest current threshold value for any sensed muscle atthat given point in time. The dial 2201 includes the threshold value inlarge text 2202 and a gauge arrow 2204 that points to the thresholdvalue on a semi-circular scale 2206. The background color 2208 of thedial 2201 may change according to predetermined range definitions. Incertain embodiments, the predetermined range definitions may beconfigured in a setup screen discussed in detail in FIG. 34. Second, asshown in FIG. 26, the surgeon view 2200 displays the individual musclethresholds via horizontal bar graphs 2220, 2222, 2224 on the left andright sides (or on any other suitable side) of the dial 2201. As thethreshold for activating a muscle response decreases, the bar increasesin size along the direction A shown by the decreasing threshold arrow.In certain embodiments, the bar 2220, 2222, 2224 changes from green toyellow to red (or any other suitable color), as the threshold decreasesthrough the threshold ranges. In certain embodiments, the surgeon dialwindows are user-configurable to change the relative size of therespective windows.

In certain embodiments, the dial 2201 can be used to indicate to thesurgeon the absolute distance to a proximal nerve. Similar to the mannerin which the dial 2201 indicates the lowest threshold for any sensedmuscle, the dial 2201 may include the distance value in large text 2202and a gauge arrow 2204 that points to the distance value on asemi-circular scale 2206. The background color 2208 of the dial 2201 maychange according to predetermined range definitions. In certainembodiments, the predetermined range definitions may be configured in asetup screen.

Furthermore, in certain embodiments, the dial 2201 can be used toindicate to the surgeon the direction of a proximal nerve. For example,a directional indicator 2210 may be displayed with the dial 2201 toindicate the relative direction of the proximal nerve with respect tothe travel of the probe in three-dimensions including superior (a),inferior (b), medial (c), lateral (d), anterior (e), and posterior (f)directional indicators. Any suitable technique may be used fordetermining the location of a nerve. Mapping the location of nerves isdiscussed in detail in Cadwell U.S. Patent Application Publication No.2012/0109004, filed Oct.27, 2010, the disclosure of which is herebyincorporated by reference herein in its entirety.

Various surgeon views 2260, 2270, 2280, 2290 are depicted in FIGS. 27-30to illustrate exemplary changes to the dial that can occur during asurgical procedure. As shown in FIG. 27, when the selected surgical modeis running but the stimulus loop is not closed (e.g., the probe or otherinstrument is not touching the patient), the dial indicates “No Stim.”As shown in FIG. 28, when the stimulus loop is closed, but the algorithmhas not yet identified a threshold, the dial indicates “Searching.” Asshown in FIG. 29, when the algorithm reaches its maximum stimulus levelwithout identifying a threshold, the dials indicates “>MAX,” where MAXis the maximum stimulus level for the mode, depicted as 20 mA in thefigure. As shown in FIG. 30, when the algorithm has detected the minimumlevel required to produce a threshold crossing, that level is displayedand the background color of the dial may be adjusted as necessary.

The monitorist view displays detailed information to the technician ormonitorist, including the raw waveform responses for each sensed muscle.As discussed above, the monitorist view may include the waveformresponses to the current stimulus while the surgeon view does not;instead including numeric and/or graphical indicators of distance and orcurrent amplitude based on the same waveform responses. The detailedinformation provided to the monitorist allows the monitorist todetermine, for example, whether the information is reliable (e.g., bychecking for artifacts or other signal noise) and adjust the settings ofthe monitoring system pre, post, or intraoperatively. As shown in FIG.31, for example, the monitorist view 2300 includes waveform responsesand each sensed muscle has its own sub-window in the monitorist view.Eight sub-windows 2301-2308 are shown in the figure, one for each sensedmuscle of the right and left leg, although any suitable number ofsub-windows may be used. Responses within the monitorist view 2300 areupdated approximately once per second. The stimulus level associatedwith each waveform is displayed via a colored watermark 2310 in thebackground of the window 2305 for that muscle. The waveforms displayedin each window (e.g., waveform 2312 of window 2305) may be determinedbased on a “threshold crossing” or a “response to last stimulus.” Athreshold crossing occurs if the corresponding muscle evoked asuprathreshold response, and in such cases the response at the thresholdvalue is displayed. A response to last stimulus occurs if thecorresponding muscle did not evoke a suprathreshold response, and insuch cases the response at the highest stimulus level is displayed. Asan example, assume that the algorithm stimulated at 5, 6, 7, 8, and 9 mAduring the one second period. The left quadriceps crossed the thresholdat 6 mA, but none of the other muscles responded to any of the stimuluspulses. The left quad window would display its response at 6 mA, whilethe other muscle windows would display their responses at 9 mA. It isunderstood that displays are referred to as “monitorist views” or“surgeon views” in order to simplify the discussion and that anyspecific display may be viewed by a monitorist, surgeon, or otherpersonnel associated with the surgical procedure.

Within the windows 2301-2308 for each muscle, there is a pair ofhorizontal dashed lines (e.g., lines 2314 and 2316 of window 2306) thatrepresent the response amplitude threshold for that muscle. Responsesthat cross this dashed line in either the positive or negative directionwill be counted by the algorithm as threshold responses. In certainembodiments, each channel has an independent response amplitudethreshold. The response amplitude threshold can be adjusted by selectingone of the horizontal dashed lines and moving it up or down. The newresponse amplitude threshold level is indicated by the decorator in thetop-right corner of that window. As shown in FIG. 32, the dashed lines2402, 2404 of a given sub-window 2400 can be moved up or down along thedirections of arrow B.

Within the windows 2301-2308 for each muscle, there is also a pair ofvertical dashed lines (e.g., lines 2318 and 2320 of window 2306) thatrepresent periods of time that are ignored by the algorithm.Specifically, any threshold crossings that occur before the left-mostdashed line 2318 are considered stimulus artifact and not a true muscleresponse. Any threshold crossings that occur after the right-most dashedline 2320 are considered baseline drift artifact and not a true muscleresponse. As shown in FIG. 33, the dashed lines 2452, 2454 of a givensub-window 2450 can be moved along the directions of arrows C and D.

In certain embodiments, threshold ranges are used to determine thecolors displayed on the surgeon dial view and the audio tones that areplayed during the surgical procedure. These ranges can be adjusted bythe monitorist or the surgeon. Any suitable threshold ranges may beused. For example, in certain embodiments where the maximum stimuluslevel is set at 20 mA, default threshold ranges of 0-5 mA, 5-10 mA, andgreater than 10 mA may be used for color indications that are red,yellow, and green, respectively. Audio tones may accompany theprocedure, and in certain embodiments a green threshold results in asingle tone that repeats once every two seconds. For the yellowthreshold, a single tone is produced at a relatively higher pitch,level, and repetition rate than the green tone. For the red threshold, asingle tone is produced at a high pitch, level, and repetition rate thanthe yellow tone. It will be understood that any suitable color and/oraudio scheme can be used to provide feedback to the surgeon during thesurgical approach. As shown in FIG. 34, a threshold display screen 2500may be displayed that allows the user to change the threshold ranges forthe red 2502, yellow 2504, and green 2506 zones. In certain embodiments,the user can slide the respective threshold values up or down along thedirections of arrow E. In certain embodiments, the user can change thethreshold values by manually entering the desired threshold values(e.g., using the user interface 2016 of FIG. 20).

The foregoing is merely illustrative of the principles of thedisclosure, and the systems, devices, and methods can be practiced byother than the described embodiments, which are presented for purposesof illustration and not of limitation. It is to be understood that thesystems, devices, and methods disclosed herein, while shown for use inspinal surgical procedures, may be applied to systems, devices, andmethods to be used in other surgical procedures performed in theproximity of neural structures where nerve avoidance, detection, ormapping is desired, including, but not limited to selected brainsurgeries, carotid endarterectomy, otolaryngology procedures such asacoustic neuroma resection, parotidectomy, nerve surgery, or any othersurgical procedures.

Variations and modifications will occur to those of skill in the artafter reviewing this disclosure. The disclosed features may beimplemented, in any combination and subcombination (including multipledependent combinations and subcombinations), with one or more otherfeatures described herein. The various features described or illustratedabove, including any components thereof, may be combined or integratedin other systems. Moreover, certain features may be omitted or notimplemented.

Examples of changes, substitutions, and alterations are ascertainable byone skilled in the art and could be made without departing from thescope of the information disclosed herein. All references cited hereinare incorporated by reference in their entirety and made part of thisapplication.

What is claimed is:
 1. A method for neuromonitoring, comprising:delivering a first stimulus signal having a first amplitude and a secondstimulus signal having a second amplitude to tissue including oradjacent to a nerve, the first amplitude being different from the secondamplitude; detecting, at one or more sensors associated with muscletissue, a first neuromuscular response in response to the first stimulussignal and a second neuromuscular response in response to the secondstimulus signal; calculating a stimulation threshold for the nerve fromthe first and second stimulus signal amplitudes and the first and secondneuromuscular responses, the stimulation threshold being an estimate ofa minimum stimulus level required to elicit a neuromuscular responsegreater than or equal to a predetermined threshold; and communicating toa user an indicator of the stimulation threshold to indicate at leastone of nerve proximity and pedicle integrity.
 2. The method of claim 1,wherein each of the first and second neuromuscular responses is greaterthan or equal to the predetermined threshold.
 3. The method of claim 1,wherein one of the first and second neuromuscular responses is greaterthan or equal to the predetermined threshold, and the other of the firstand second neuromuscular responses is less than the predeterminedthreshold.
 4. The method of claim 1, wherein the first and secondneuromuscular responses are detected using electromyography (EMG), andthe predetermined threshold corresponds to a voltage level of detectedEMG signals.
 5. The method of claim 1, wherein the first and secondneuromuscular responses are detected using EMG, and the predeterminedthreshold corresponds to a level of a correlation function calculatedfrom detected EMG signals.
 6. The method of claim 5, further comprisingcross-correlating the detected EMG signals with an EMG responsetemplate, wherein the predetermined threshold is a level of acorrelation function between the detected EMG signals and the EMGresponse template.
 7. The method of claim 1, wherein the calculatingstep comprises: calculating a linear function from the first and secondstimulus signal amplitudes and the first and second neuromuscularresponses; and determining the stimulation threshold from the linearfunction.
 8. The method of claim 1, wherein the calculating stepcomprises: calculating a curve fit from the first and second stimulussignal amplitudes and the first and second neuromuscular responses; anddetermining the stimulation threshold from the curve fit.
 9. The methodof claim 8, wherein the curve fit is a sigmoid function.
 10. The methodof claim 1, further comprising delivering a plurality of test stimulussignals to the tissue and detecting a plurality of test neuromuscularresponses, each of the plurality of test neuromuscular responsescorresponding to one of the plurality of test stimulus signals.
 11. Themethod of claim 10, wherein each of the plurality of test stimulussignals has an amplitude that is greater than a preceding test stimulussignal.
 12. The method of claim 11, wherein the amplitudes of theplurality of test stimulus signals increase at a constant increment. 13.The method of claim 11, wherein the amplitudes of the plurality of teststimulus signals increase at varying increments.
 14. The method of claim10, further comprising selecting the first and second stimulus signalsbased on the test stimulus signals and test neuromuscular responses. 15.The method of claim 14, further comprising calculating a curve fit usingthe test stimulus signals and test neuromuscular responses, andselecting the first and second stimulus signals from the curve fit. 16.The method of claim 14, wherein the first and second stimulus signalsare selected from test stimulus signals that elicit test neuromuscularresponses that meet the predetermined threshold.
 17. The method of claim14, wherein one of the first and second stimulus signals is selectedfrom test stimulus signals that elicit test neuromuscular responses thatare greater than or equal to the predetermined threshold, and the otherof the first and second stimulus signals is selected from test stimulussignals that do not elicit test neuromuscular responses that are greaterthan or equal to the predetermined threshold.
 18. The method of claim 1,wherein the first neuromuscular response is detected before the secondstimulus signal is delivered.
 19. The method of claim 18, wherein theamplitude of the second stimulus signal is adjusted based on the firstneuromuscular response.
 20. The method of claim 1, wherein the secondstimulus signal is delivered before the first neuromuscular response isdetected.
 21. The method of claim 20, wherein delivery of the first andsecond stimulus signals is offset by an amount that is greater than orequal to a refractory period of the nerve and the muscle tissue.